== CALL FOR PAPERS ==
SPECIAL SESSION ON
BUSINESS PROCESS ANALYTICS, PROCESS MINING AND PROCESS BIG DATA
2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
December 9-12, 2014, Orlando, Florida
The IEEE Task Force on Process Mining is organizing a special session at the
2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014).
The goal of this special session is to allow experts in the area of process
mining and (big) data analysis to share new techniques, applications and case
studies. Therefore, submissions of papers on new process mining techniques,
applications of process mining, business intelligence, process discovery,
conformance checking, process intelligence, big data analysis, etc. are welcome.
Process mining is a relatively young research discipline that sits between
computational intelligence and data mining on the one hand and process modeling
and analysis on the other hand. The idea of process mining is to discover,
monitor and improve real processes (i.e., not assumed processes) by extracting
knowledge from event logs readily available in today's systems.
We now live in a time where the amount of data created daily goes easily beyond
the storage and processing capabilities of nowadays systems: organizations,
governments but also individuals generate large amounts of data at a rate that
has started to overwhelm the ability to timely extract useful knowledge from it.
Nevertheless the strategic importance of the knowledge hidden in such data, for
effective decision making is paramount and need to be extracted quickly in order
to effectively react to dynamic situations. Efficient stream processing
approaches for real time analysis are crucial for enabling the predictive
capabilities required by today's dynamically and rapidly evolving enterprises.
Moreover, since the work of medium-large enterprises is typically governed by
business processes, it is very common to have event data generated as result of
such process executions that can be used as input for process mining techniques.
== TOPICS OF INTEREST ==
- Storage and extraction of big process logs
- Process mining approaches
- Online process mining (stream processing)
- Distributed approaches for process mining
- Business process intelligence
- Data mining for process management
- Specific computational intelligence applications in process mining
- Case studies
== IMPORTANT DATES ==
Paper submission: July 15, 2014
Decision: September 5, 2014
Final paper submission: October 5, 2014
== ORGANIZERS ==
Andrea Burattin, University of Padua, Italy
Fabrizio M. Maggi, University of Tartu, Estonia
Marcello Leida, Etisalat BT Innovation Centre, UAE
== MORE INFORMATION ==
Visit the conference website www.ieee-ssci.org or
http://cidm2014.processmining.it for detailed submission information.